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Athabasca University

Section 4 : Distributed CSPs

Commentary

Section Goals

  • To introduce the most recent work in distributed CSPs.

Learning Objectives

Learning Objective 1

  • Summarize the problems and techniques of distributed CSPs that are introduced in the special issue of Artificial Intelligence (see Required Readings below).
  • Identify the most interesting and the most important ideas and topics in this area.

Objective Readings

Required readings:

Faltings, B., and Yokoo, M. (eds.). (2005). Special issue: Distributed constraint satisfaction. Artificial Intelligence, 161(1-2), 1-250.

Begin by reading the first paper, then try to read as many articles as you can after that. Focus primarily on items that are of particular interest to you.

  • Faltings, B., and Yokoo, M. (2005). Introduction: Special issue on distributed constraint satisfaction. Artificial Intelligence, 161(1-2), 1-5.
  • Bessière, C., Maestre, A., Brito, I., and Meseguer, P. (2005). Asynchronous backtracking without adding links: A new member in the ABT family. Artificial Intelligence, 161(1-2), 7-24.
  • Silaghi, M.-C., and Faltings, B. (2005). Asynchronous aggregation and consistency in distributed constraint satisfaction. Artificial Intelligence, 161(1-2), 25-53.
  • Zhang, W., Wang, G., Xing, Z., and Wittenburg, L. (2005). Distributed stochastic search and distributed breakout: Properties, comparison and applications to constraint optimization problems in sensor networks. Artificial Intelligence, 161(1-2), 55-87.
  • Hirayama, K., and Yokoo, M. (2005). The distributed breakout algorithms. Artificial Intelligence, 161(1-2), 89-115.
  • Béjar, R., Domshlak, C., Fernández, C., Gomes, C., Krishnamachari, B., Selman, B., and Valls, M. (2005). Sensor networks and distributed CSP: Communication, computation and complexity. Artificial Intelligence, 161(1-2), 117-147.
  • Pragnesh, J., Modi, W.-M., Shen, M., and Tambe, M. Y. (2005). Adopt: Asynchronous distributed constraint optimization with quality guarantees. Artificial Intelligence, 161(1-2), 149-180.
  • Faltings, B., and Macho-Gonzalez, S. (2005). Open constraint programming. Artificial Intelligence, 161(1-2), 181-208.
  • Wallace, R. J., and Freuder, E. C. (2005). Constraint-based reasoning and privacy/efficiency tradeoffs in multi-agent problem solving. Artificial Intelligence, 161(1-2), 209-227.
  • Yokoo, M., Suzuki, K., and Hirayama, K. (2005). Secure distributed constraint satisfaction: reaching agreement without revealing private information. Artificial Intelligence, 161(1-2), 229-245.

Objective Questions

  • What are the main problems and techniques for distributed CSPs?
  • Why does CSP need to be expanded to distributed CSP?

Objective Activities

  • Discuss the topics and ideas about distributed CSPs that interest you in the course conference.
  • Explore the available Web resources of distributed CSPs, and share information such as links and introductions in the course conference.

Updated November 17 2015 by FST Course Production Staff